Probability Density Evolution Method for Seismic Reliability Evaluation of Structural Systems

2011 ◽  
Vol 255-260 ◽  
pp. 2606-2611
Author(s):  
Yao Long Lei ◽  
Zhang Jun Liu

A structural system reliability evaluation approach based on the idea of equivalent extreme-value event and the probability density evolution method is presented. Using the idea of equivalent extreme-value event, for a compound random event as combination of a set of random events, an equivalent extreme-value event could be constructed. So, this makes it possible to transform computation of the probability of the compound random event to a one-dimensional integration of the probability density function of the equivalent extreme-value random variable. In conjunction with the probability density evolution method, which is capable of evaluating the extreme-value distribution of a set of random variables or stochastic processes, the structural system reliability could be evaluated through computing the probability of the equivalent extreme-value event. The proposed approach is discussed in detail on how to construct the equivalent extreme-value event and then implement the procedure numerically. On the other hand, based on the orthogonal expansion method, the stochastic process of earthquake ground motion can be represented as a linear combination of deterministic functions modulated by a set of mutually independent random variables. Combining the above methods, the reliability of structures under earthquake excitations could be successfully evaluated. An example, of which deals with a linear frame structure subjected to non-stationary seismic loading, is illustrated to validate the proposed method.

2013 ◽  
Vol 569-570 ◽  
pp. 579-586 ◽  
Author(s):  
M.T. Sichani ◽  
S.R.K. Nielsen ◽  
W.F. Liu ◽  
J.B. Chen ◽  
J. Li ◽  
...  

The aim of this study is to present an efficient and accurate method for estimation of the failure probability of wind turbine structures which work under turbulent wind load. The classical method for this is to fit one of the extreme value probability distribution functions to extracted maxima of the response of wind turbine. However this approach may contain high amount of uncertainty due to arbitrariness of the data and the distributions chosen. Therefore less uncertain methods are meaningful in this direction. The most natural approach in this respect is the Monte Carlo (MC) simulation. This however has no practical interest due to its excessive computational load. This problem can alternatively be tackled if the evolution of the probability density function (PDF) of the response process can be realized. The evolutionary PDF can then be integrated on the boundaries of the problem, i.e. the exceedance threshold of the response, which results in the accurate values of the failure probability. For this reason we propose to use the probability density evolution method (PDEM). PDEM can alternatively be used to obtain distribution of the extreme values of the response process by simulation. This approach requires less computational effort than integrating the evolution of the PDF; but may have less accuracy. In this paper we present the results of failure probability estimation by the PDEM. The results will then be compared to the extrapolated values from the extreme value distribution fits to the samples response values.


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